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Linear and Non-Linear Long-Term Terrain Deformation with DInSAR

Jordi J. Mallorqui(1) and Oscar Mora(2)

(1) Universitat Politècnica de Catalunya (UPC), D3-Campus Nord-UPC, 08034 Barcelona, Spain
(2) Insritut Cartogràfic de Catalunya (ICC), Parc de Montjuïc, 08038 Barcelona, Spain


Jordi J. Mallorquí, Pablo Blanco, Oscar Mora, Antoni Broquetas Dept. of Signal Theory and Communications Universitat Politècnica de Catalunya (UPC) D3-Campus Nord-UPC C/ Jordi Girona 1-3, 08034 Barcelona, Spain

In this paper, an advanced technique for the generation of deformation maps developed under the scope of ESA AO3 421 Project is presented. The technique has been tested with data from an area of Catalonia (Spain) affected by subsidence and validated with on-field precise levelling measurements.

The developed algorithm is able to retrieve the linear and non-linear components of movement from a set of low resolution interferograms (multilooked), estimating at the same time the DEM error and the atmospheric artifacts. The basis for the linear estimation of movement is the adjustment of a linear model, which considers the linear velocity of displacement and the DEM error, to the available data in a similar way as done in the preceding methods. The pixel selection criterion is based on its coherence stability in the stack of interferograms, in consequence the final product will have lower resolution than the original images and interferograms with short baselines will be preferred but this restriction is not compulsory. Besides this, the generation of the interferograms does not require establishing a master image, allowing free combinations of all available images. These two characteristics enable the algorithm to work with a small number of images, if compared with the requirements of the PS technique for instance. Preliminary experiments provided good deformation maps from a reduced set of only seven images, these results were very similar to the ones obtained later on from a larger dataset of twenty images of the same zone. This flexibility allows the user to generate deformation maps at a reduced cost and once a problematic zone is detected to plan the acquisition of more images. The method adjusts a linear model to phase increments between two neighboring pixels linked with the Delauney triangulation, avoiding the need of a sparse grid phase unwrapping of the interferograms.

Once the linear velocity of deformation and the DEM error have been retrieved, the algorithm continues with the non-linear movement and the atmospheric artifacts estimation. In essence the algorithm takes advantage of the different behavior of the atmospheric artifacts in time and space with respect the non-linear movement to isolate their respective contributions to the phase. Although the approach is similar in philosophy to other methods, the practical implementation is different and oriented to strengthen the algorithm robustness. A combination of temporal and spatial filters sequentially applied are able to extract the atmospheric artifacts and the low and high pass components of the non-linear movement. As the interferograms were generated freely from the available images, the SVD method is used to retrieve the temporal sequence suitable for the temporal filtering. One of the advantages of the algorithm is that there is no need to unwrap the noisy differential interferograms, which can be a difficult step and a potential source of errors. In addition the SVD method provides a minimum norm solution and allows the connection among non-connected subsets of interferograms, however some fast non-linear movements could be underestimate. The coupling of the atmosphere and the non-linear movement, as both can present a similar phase behavior, is a common limitation in all methods.

The results obtained with the algorithm and the dataset will be presented and discussed in the paper.


Workshop presentation

Full paper

Keywords: ESA European Space Agency - Agence spatiale europeenne, observation de la terre, earth observation, satellite remote sensing, teledetection, geophysique, altimetrie, radar, chimique atmospherique, geophysics, altimetry, radar, atmospheric chemistry